The Deep Blue Team Plots Its Next Move

It was a classic match of man versus machine: In February 1996,
world champion chess player Gary Kasparov pitted his wits against
Deep Blue, a computer designed by a team of computer scientists
from IBM. Deep Blue took the first game, but Kasparov recovered and
ended up winning the match 4 games to 2. Three weeks later, John
Horgan of Scientific American interviewed the Deep Blue team at the
IBM Thomas J. Watson Research Center in Yorktown Heights, New
York.

Present during the interview were Chung-Jen Tan, manager of
the Deep Blue team; Feng-hsiung Hsu, who designed Deep Blue's
predecessor, Deep Thought, when he was a graduate student at
Carnegie Mellon University in the mid-1980s; Murray Campbell, who
also worked on Deep Thought at Carnegie Mellon and is the IBM
team's best chess player; Joseph Hoane, a programmer; and Marcy
Holle, an IBM public relations manager. Absent were Jerry Brody,
another programmer who had been delayed by an ice storm; and
Deep Blue itself, a brace of refrigerator-sized IBM SP 2 computers,
each containing 16 parallel processors, which remained housed in its
room elsewhere in the building.

A slightly edited transcript of the interview follows.

SCIENTIFIC AMERICAN: Some news reports suggested that Deep Blue
might have lost the match because of human error, such as your
tinkering with Deep Blue's program between match one, which Deep
Blue won, and match two, which the computer lost.

Campbell: "That had no influence... there were no errors of
any
consequence in the second game."

Hoane: "Yeah, the only human error was the draw in game
five." [Early in game five, Kasparov offered Deep Blue a draw. The
computer's managers rejected the offer, and Kasparov went on to win the match.]

Campbell: "But that's not a human error. The computer doesn't ever accept draws. If we want to, we can accept a draw, but it will never accept a draw. It's in the rules."

Tan: "Offering of draws generally happens when things are
very close, unless it's a repetition of some sort. Otherwise the
computer will just keep going. [Kasparov] offered a draw because he
saw he had no chance of winning and he wanted to do better next
game... We just made a decision."

Campbell: "If we'd won everybody would have said we were
brilliant."

SCIENTIFIC AMERICAN: So you are not second-guessing yourself
about your strategy during the match with Kasparov?

Campbell: "At the time we did what we thought was the right
thing to do... "

Tan: "It was really early in the game, move 23, and there was
no indication one way or the other about which side had the
advantage."

Hoane: "You've got to understand how tough it is for us to get
a
good game out of a grandmaster. They don't give you their best
unless there's money on the line."

Campbell: "When you're playing against the world champion,
and you're not losing, you might as well play it out."

SCIENTIFIC AMERICAN: Was Kasparov finding weaknesses in Deep
Blue over the course of the match?

Tan: "Not only weaknesses. He found how strong the machine
was, therefore he changed the style of play and the strategy of play.
He said the first game he lost was the best thing that ever happened
to him, because otherwise [his initial strategy] would have come back
to haunt him in later games."

Campbell: "He might have lost at a critical time later on instead
of in the beginning when he could recover."

SCIENTIFIC AMERICAN: So if the match had continued, would
Kasparov have kept getting winning more and more easily?

Tan: "It's hard to tell, because he could get more tired and
nervous... and [Deep Blue] will stay very strong. And he may get a
couple of games where, if he loses to Deep Blue, he would feel
tremendous pressure on him."

Hoane: "Plus he may have learned everything he could learn [in
the first six games]. It's not clear."

Campbell: "It's also possible that we could change the program
too [to alter its strategy between games]. We were very conservative
about changing the program, because in such a short time when you
make a change you can't really test it thoroughly. But in theory, if we
see the same thing happening over and over, we can change it. We
can patch holes. We didn't do that, but we are allowed to."

SCIENTIFIC AMERICAN: Did you think you would win the match?

Campbell: "Some people were predicting Kasparov would win
six-zero, and some people were predicting we would win by a large
margin. I had strong feelings going into the match that we would be
as good as Kasparov. The problem going into the match is, the
computer and the world champion just have such different strengths,
different weaknesses. It's hard to see how this is going to match up.
The computer has the power of calculating..., being 'like God,' in
certain positions, to use Kasparov's words. And Kasparov has all this
intuition and understanding of chess and all the things that he's good
at. It wasn't clear how it was going to come together, what strengths
would play against what weaknesses. And the answer is, it happened
many different ways, and it looks like a respectable, perhaps equal
challenge we gave him."

SCIENTIFIC AMERICAN: In an article published in Scientific American in October 1990, Hsu, Campbell and two colleagues that
are no longer involved in the chess project predicted that the
computer would have a rating of 3,200, much higher than Kasparov's
rating of 2,800, by 1992. Why hasn't that happened yet?
Tan: "The truth of the matter is, our project did take longer
than expected."

Campbell: "Also, we never predicted a 3,200 rating for
ourselves. There's a graph in the Scientific Americanarticle
which a lot of people misinterpreted... There were some very careful
words, we thought, qualifying that [prediction]. 'If present trends
continue, and assuming this and assuming that.'"

Tan: "We went into this match with the goal of playing
somewhere like 2,800... And I think we did pretty well, as far as
getting to that level... We didn't win the match, but it was a very
close encounter, especially the first game. If we patched up some
potholes, we could have easily turned the match around."

SCIENTIFIC AMERICAN: Does the computer always make the same
move when faced with a given position?

Hsu: "There is some randomization by the fact we are doing a parallel search... Sometime the same position, the same program, the
same hardware, everything the same, start it again, it might behave
differently."

[MARCY HOLLE, the IBM public relations spokesperson, suggests that
the Deep Blue team explain why Deep Blue made certain moves in its
first game against Kasparov.]

Campbell: "It's hard to explain what it did, because it is a
20
billion move search, or something like that."

Hsu: "And we can only see... one line of moves."

Tan: "... It's hard to even just record and look at 20 billion
board positions. So the computer just prints out the principal line of
its search. The machine is very accurate [in its analysis of certain
situations], because it looks at all possible moves up to 12 ply and
others down further. So when Gary was trying to checkmate Deep
Blue at the end of game one, the computer just saw every move and
was one step ahead of him [and could ignore the threat]... A human
player... would have been scared."

Hoane: "The machine is always blithe."

Campbell: "You can't bluff it."

Hsu: "You can say that Kasparov lost the first game, maybe,
because of lack of experience in playing with a machine. And we lost
the last two games because of lack of experience..."

SCIENTIFIC AMERICAN: Will Deep Blue and Kasparov play again
anytime soon?

Holle: "We're negotiating that with him at the moment. He
wants it, he asked for it."

Tan: "He got more exposure out of the match than any other
match."

SCIENTIFIC AMERICAN: Why has it taken so long for a computer to
surpass all humans in chess, which seems like such a perfect game
for a computer to play?

CAMPBELL: "The reason chess is interesting is, it's not perfect for a human and it's not perfect for a computer. It's somewhere in
the middle. Games like checkers... at this point have been mastered
by a machine, [whereas in the game of Go] people are so far ahead
it's just not interesting. But chess is an interesting game because
there are elements of calculation, there are elements of intuition and
pattern recognition, all the traditional AI [artificial intelligence] stuff,
and all sort of clashing. It hasn't been resolved one way or the other
yet."

SCIENTIFIC AMERICAN: Does the difficulty that you have had in
beating human players in chess suggest something about the limits of
artificial intelligence (AI)? Aren't other problems in AI, such as
speech recognition, much harder than chess?

Tan: "This chess project is not AI. In the early days people
used
chess to demonstrate AI techniques, but in the late 1970s and early
'80s people started to realize that [if you reduce chess to a problem
in pure computation rather than one of judgment and intuition], then
you can really get much better results from a computer. Before you
understand the problem, you call it AI, but once you really
understand it you can reduce that to a computation algorithm."
SCIENTIFIC AMERICAN: If chess can be reduced to computation, why
has it been so hard to beat a human like Kasparov?

Campbell: "Because there are some things that people can do
that we haven't been able to reduce to computation."

Tan: "And it's also taken this long for the computer technology
to give us the computational power to do that. Without the
architecture, without the parallel processor we developed, you
cannot do it."

Campbell: "The amazing thing is that it requires that much
computation to get close to beating the best people... Nobody would
have guessed in the mid-1950s that it would take 100 million
positions per second to play close to the level of the world
champion."

Hoane: "The techniques that tried to mimic human judgment
failed miserably. We still don't know how to do that at all."

SCIENTIFIC AMERICAN: How long will the Deep Blue project
continue?

Tan: "This is really part of the overall research to understand
how to use parallel processing's computational capability to solve
complex problems. We have many activities going on, and chess is
one of them. When we get to a point where we think we understand
enough from chess to derive benefit from it for improving our
understanding of parallel processing, we will stop. Gradually, when
chess is no longer interesting, we will completely stop and move onto
other areas. But it will be a smooth transition. It will not be
something that stops tomorrow."

Campbell: "When we say, 'Chess is no longer interesting,' we
mean, 'Chess is no longer interesting from a computer-science
research point of view.' Obviously we have no intention of making
chess uninteresting for chess players!"

SCIENTIFIC AMERICAN: How do you feel about the press portraying
Deep Blue as the modern equivalent of the machine that took over
the job of John Henry, the legendary railroad worker?
Hoane: "A lot of miners don't have black lung disease because
machines do the work for them."

Hsu: "... This is not just a simple tool like the steam engine...
This is a big challenge from a computer science point of view. When
Gary won the match, everybody applauded, and we applauded with a
different perspective, because we knew what Gary went through..."

Hoane: "I got one little gee whiz number. How long has
[Kasparov] been playing chess? Twenty-eight years or so. And how
long have we been playing chess [in total]? About 25 years... The
human effort that went into this event was the same, in a sense..."

Tan: "It is really just one person using a brain versus many
people using a tool."

SCIENTIFIC AMERICAN: When will Deep Blue beat Kasparov?

Tan: "We already did once!"

Hsu: "There's always an element of chance, In fact, even in
this
match we had some good chance of winning....It could happen next
time even with the same machine..."

SCIENTIFIC AMERICAN: Is it just a matter of time before Deep Blue
defeats Kasparov easily? [Everyone nods]

Tan: "In this match we used a 32-node parallel processor...
We have in this building a 128-node parallel processor. We did not use
that one, because it is very expensive... [We would have] to stop all
other research in this building. That's one thing. Secondly, our goal is
just to get to the level where we can play Gary... We did that. If we
really wanted 100-percent certainty that we will beat him in a
match, we would have used 128 or 512[-node] parallel system to get
extra insurance. But we didn't do that. So the technology is here
today, in terms of computational strength."

Campbell: "If we hired ten grandmasters for two years to help
us and we got the biggest machines and spent hundreds of millions
of dollars, I think we could have done it. But what we're learning just
as much from what we're doing."

Holle: "Chess is the perfect model for taking parallel processing
and understanding it, for taking it to various applications. That's
what this is all about. Because, this is IBM."

Tan: "You can talk about the so-called upper limits, the electron
and so forth... But advances will be made in other areas, such as
software... It's hard to say where the limit will be."

SCIENTIFIC AMERICAN: Will computers someday be able to emulate
every human attribute?

Campbell: "Of course, in principle. You just emulate [the brain]
neuron for neuron, device for device, but that's like centuries in the
future."

Tan: "It's more than that. Yeah, you can substitute electrons
for neurons, but the brain is more than hardware. It's all the software
and everything else. I'm not a psychologist or a neurologist, but I'm
sure they don't understand those problems either."